Search results for: Information Gain Ratio

Authors: E. Moroydor Derun, A. S. Kipcak, A. Kaplan, S. Piskin

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Magnesium wastes are produced by many industrial activities. This waste problem is becoming a future problem for the world. Magnesium borates have many advantages such as; high corrosion resistance, heat resistance, high coefficient of elasticity and can also be used in the production of material against radiation. Addition, magnesium borates have great potential in sectors including ceramic and detergents industry and superconducting materials. In this study, using the starting materials of waste magnesium and H3BO3 the hydrothermal method was applied at a moderate temperature of 70oC. Several mole ratios of waste magnesium to H3BO3 are selected as; 1:2, 1:4, 1:6, 1:8, 1:10. Reaction time was determined as 1 hour. After the synthesis, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques are applied to products. As a result the forms of mcallisterite “Mg2(B6O7(OH)6)2.9(H2O)”, admontite “MgO(B2O3)3.7(H2O)” and magnesium boron hydrate (MgO(B2O3)3.6(H2O)” are obtained. 

Keywords: Hydrothermal synthesis, magnesium borates, waste magnesium.

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Authors: Antigoni Panagiotopoulou, Lemonia Ragia

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High-resolution satellite images can provide detailed information about change detection on the earth. In the present work, QuickBird images of spatial resolution 60 cm/pixel and WorldView images of resolution 30 cm/pixel are utilized to perform automatic change detection in urban and suburban areas of Crete, Greece. There is a relative time difference of 13 years among the satellite images. Multiindex scene representation is applied on the images to classify the scene into buildings, vegetation, water and ground. Then, automatic change detection is made possible by pixel-per-pixel comparison of the classified multi-temporal images. The vegetation index and the water index which have been developed in this study prove effective. Furthermore, the proposed change detection approach not only indicates whether changes have taken place or not but also provides specific information relative to the types of changes. Experimentations with other different scenes in the future could help optimize the proposed spectral indices as well as the entire change detection methodology.

Keywords: Change detection, multiindex scene representation, spectral index, QuickBird, WorldView.

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Authors: S. H. Anilkumar, Ghulam Jilani

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The objective of the present work is to conduct investigations leading to a more complete explanation of single phase natural convective heat transfer in an enclosure with fin utilizing nano fluids. The nano fluid used, which is composed of Aluminum oxide nano particles in suspension of Ethylene glycol, is provided at various volume fractions. The study is carried out numerically for a range of Rayleigh numbers, fin heights and aspect ratio. The flow and temperature distributions are taken to be two-dimensional. Regions with the same velocity and temperature distributions are identified as symmetry of sections. One half of such a rectangular region is chosen as the computational domain taking into account the symmetry about the fin. Transport equations are modeled by a stream functionvorticity formulation and are solved numerically by finite-difference schemes. Comparisons with previously published works on the basis of special cases are done. Results are presented in the form of streamline, vector and isotherm plots as well as the variation of local Nusselt number along the fin under different conditions.

Keywords: Fin height, Nano fluid, natural convection, Rayleigh number.

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Authors: Abu Rayhan Md. Ali, Nidul Ch. Ghosh, Tanvir-E-Alam

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The effect of autofrettage process in strain hardened thick-walled pressure vessels has been investigated theoretically by finite element modeling. Equivalent von Mises stress is used as yield criterion to evaluate the optimum autofrettage pressure and the optimum radius of elastic-plastic junction. It has been observed that the optimum autofrettage pressure increases along with the working pressure. For two different working pressures, the effect of the ratio of outer to inner radius (b/a=k) value on the optimum autofrettage pressure is also noticed. The Optimum autofrettage pressure solely depends on K value rather than on the inner or outer radius. Furthermore, percentage reduction of von Mises stresses is compared for different working pressures and different k values. Maximum von Mises stress developed at different autofrettage pressure is equated for elastic perfectly plastic and elastic-plastic material with different slope of strain hardening segment. Cylinder material having higher slope of strain hardening segment provides better benedictions in the autofrettage process.

Keywords: Autofrettage, elastic plastic junction, pressure vessel, von Mises stress.

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Authors: Chandrakala Varatharajoo, Adelina Binti Asmawi, Nabeel Abdallah Mohammad Abedalaziz

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This study investigated the impact of inflectional and derivational morphemic analysis awareness on ESL secondary school students’ vocabulary learning strategy. The quasi-experimental study was conducted with 106 low proficiency secondary school students in two experimental groups (inflectional and derivational) and one control group. The students’ vocabulary acquisition was assessed through two measures: Morphemic Analysis Test and Vocabulary- Morphemic Test in the pretest and posttest before and after an intervention programme. Results of ANCOVA revealed that both the experimental groups achieved a significant score in Morphemic Analysis Test and Vocabulary-Morphemic Test. However, the inflectional group obtained a fairly higher score than the derivational group. Thus, the results indicated that ESL low proficiency secondary school students performed better on inflectional morphemic awareness as compared to derivatives. The results also showed that the awareness of inflectional morphology contributed more on the vocabulary acquisition. Importantly, learning inflectional morphology can help ESL low proficiency secondary school students to develop both morphemic awareness and vocabulary gain. Theoretically, these findings show that not all morphemes are equally useful to students for their language development. Practically, these findings indicate that morphological instruction should at least be included in remediation and instructional efforts with struggling learners across all grade levels, allowing them to focus on meaning within the word before they attempt the text in large for better comprehension. Also, by methodologically, by conducting individualized intervention and assessment this study provided fresh empirical evidence to support the existing literature on morphemic analysis awareness and vocabulary learning strategy. Thus, a major pedagogical implication of the study is that morphemic analysis awareness strategy is a definite boon for ESL secondary school students in learning English vocabulary.

Keywords: ESL, instruction, morphemic analysis, vocabulary.

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Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: Data fusion, Dempster-Shafer theory, data mining, event detection.

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Authors: Michael J. Hamlin, Apiwan Manimmanakorn, Gavin R. Sandercock, Jenny J. Ross, Robert H. Creasy, John Hellemans

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The aim of this study was to compare the effects of an altitude training camp on heart rate variability and performance in elite triathletes. Ten athletes completed 20 days of live-high, train-low training at 1650m. Athletes underwent pre and post 800-m swim time trials at sea-level, and two heart rate variability tests at 1650m on the first and last day of the training camp. Based on their time trial results, athletes were divided into responders and non-responders. Relative to the non-responders, the responders sympathetic-toparasympathetic ratio decreased substantially after 20 days of altitude training (-0.68 ± 1.08 and -1.2 ± 0.96, mean ± 90% confidence interval for supine and standing respectively). In addition, sympathetic activity while standing was also substantially lower post-altitude in the responders compared to the non-responders (-1869 ± 4764 ms2). Results indicate that responders demonstrated a change to more vagal predominance compared to non-responders.

Keywords: parasympathetic predominance, poor performance, triathlon, 800-m swim

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Authors: Theodore Grosch, Felipe Koji Godinho Hoshino

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In wireless communications, 3GPP LTE is one of the solutions to meet the greater transmission data rate demand. One issue inherent to this technology is the PAPR (Peak-to-Average Power Ratio) of OFDM (Orthogonal Frequency Division Multiplexing) modulation. This high PAPR affects the efficiency of power amplifiers. One approach to mitigate this effect is the Crest Factor Reduction (CFR) technique. In this work, we simulate the impact of Hard Limited Clipping Crest Factor Reduction technique on BER (Bit Error Rate) in OFDM based Systems. In general, the results showed that CFR has more effects on higher digital modulation schemes, as expected. More importantly, we show the worst-case degradation due to CFR on QPSK, 16QAM, and 64QAM signals in a linear system. For example, hard clipping of 9 dB results in a 2 dB increase in signal to noise energy at a 1% BER for 64-QAM modulation.

Keywords: Bit error rate, crest factor reduction, OFDM, physical layer simulation.

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Authors: Irfan Z. Qureshi, Fareeha A., Wajid A. Khan

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Human amniotic membrane (HAM) is a useful biological material for the reconstruction of damaged ocular surface. The processing and preservation of HAM is critical to prevent the patients undergoing amniotic membrane transplant (AMT) from cross infections. For HAM preparation human placenta is obtained after an elective cesarean delivery. Before collection, the donor is screened for seronegativity of HCV, Hbs Ag, HIV and Syphilis. After collection, placenta is washed in balanced salt solution (BSS) in sterile environment. Amniotic membrane is then separated from the placenta as well as chorion while keeping the preparation in BSS. Scrapping of HAM is then carried out manually until all the debris is removed and clear transparent membrane is acquired. Nitrocellulose membrane filters are then placed on the stromal side of HAM, cut around the edges with little membrane folded towards other side making it easy to separate during surgery. HAM is finally stored in solution of glycerine and Dulbecco-s Modified Eagle Medium (DMEM) in 1:1 ratio containing antibiotics. The capped borosil vials containing HAM are kept at -80°C until use. This vial is thawed to room temperature and opened under sterile operation theatre conditions at the time of surgery.

Keywords: HAM, AMT, ocular transplant

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Authors: Berkay Ergene, Çağın Bolat

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In this study, we mainly focused on a simulation study regarding composite footbed in order to contribute to shoe industry. As a footbed, e-glass fiber reinforced polyurethane was determined since polyurethane based materials are already used for footbed in shoe manufacturing frequently. Flat, elliptical and rectangular grooved shoe soles were modeled and analyzed separately as TPU, 10% glass fiber reinforced, 30% glass fiber reinforced and 50% glass fiber reinforced materials according to their properties under three point bending and compression situations to determine the relationship between model, material type and mechanical behaviours of composite model. ANSYS 14.0 APDL mechanical structural module is utilized in all simulations and analyzed stress and strain distributions for different footbed models and materials. Furthermore, materials constants like young modulus, shear modulus, Poisson ratio and density of the composites were calculated theoretically by using composite mixture rule and interpreted for mechanical aspects.

Keywords: Composite, elastic behaviour, footbed, simulation.

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Authors: Niaz Gharavi, Hexin Zhang, Yanjun Xie

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The timber beam end effect in the torsion test is evaluated using binocular stereo vision system. It is recommended by BS EN 408:2010+A1:2012 to exclude a distance of two to three times of cross-sectional thickness (b) from ends to avoid the end effect; whereas, this study indicates that this distance is not sufficiently far enough to remove this effect in slender cross-sections. The shear modulus of six timber beams with different aspect ratios is determined at the various angles and cross-sections. The result of this experiment shows that the end affected span of each specimen varies depending on their aspect ratios. It is concluded that by increasing the aspect ratio this span will increase. However, by increasing the distance from the ends to the values greater than 6b, the shear modulus trend becomes constant and end effect will be negligible. Moreover, it is concluded that end affected span is preferred to be depth-dependent rather than thickness-dependant.

Keywords: End effect, structural-size torsion test, shear properties, timber engineering, binocular stereo vision.

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Authors: Asif Ekbal, Sivaji Bandyopadhyay

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Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is now-a-days considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali and Hindi using Support Vector Machine (SVM). Though this state of the art machine learning technique has been widely applied to NER in several well-studied languages, the use of this technique to Indian languages (ILs) is very new. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the four different named (NE) classes, such as Person name, Location name, Organization name and Miscellaneous name. We have used the annotated corpora of 122,467 tokens of Bengali and 502,974 tokens of Hindi tagged with the twelve different NE classes 1, defined as part of the IJCNLP-08 NER Shared Task for South and South East Asian Languages (SSEAL) 2. In addition, we have manually annotated 150K wordforms of the Bengali news corpus, developed from the web-archive of a leading Bengali newspaper. We have also developed an unsupervised algorithm in order to generate the lexical context patterns from a part of the unlabeled Bengali news corpus. Lexical patterns have been used as the features of SVM in order to improve the system performance. The NER system has been tested with the gold standard test sets of 35K, and 60K tokens for Bengali, and Hindi, respectively. Evaluation results have demonstrated the recall, precision, and f-score values of 88.61%, 80.12%, and 84.15%, respectively, for Bengali and 80.23%, 74.34%, and 77.17%, respectively, for Hindi. Results show the improvement in the f-score by 5.13% with the use of context patterns. Statistical analysis, ANOVA is also performed to compare the performance of the proposed NER system with that of the existing HMM based system for both the languages.

Keywords: Named Entity (NE), Named Entity Recognition (NER), Support Vector Machine (SVM), Bengali, Hindi.

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Authors: C. G. Jinimole, A. Harsha

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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: Computed tomography, enhancement techniques, increasing contrast, PSNR and MSE.

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Authors: Omer Nebil Yaveroglu, Tolga Can

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In this study, a high accuracy protein-protein interaction prediction method is developed. The importance of the proposed method is that it only uses sequence information of proteins while predicting interaction. The method extracts phylogenetic profiles of proteins by using their sequence information. Combining the phylogenetic profiles of two proteins by checking existence of homologs in different species and fitting this combined profile into a statistical model, it is possible to make predictions about the interaction status of two proteins. For this purpose, we apply a collection of pattern recognition techniques on the dataset of combined phylogenetic profiles of protein pairs. Support Vector Machines, Feature Extraction using ReliefF, Naive Bayes Classification, K-Nearest Neighborhood Classification, Decision Trees, and Random Forest Classification are the methods we applied for finding the classification method that best predicts the interaction status of protein pairs. Random Forest Classification outperformed all other methods with a prediction accuracy of 76.93%

Keywords: Protein Interaction Prediction, Phylogenetic Profile, SVM , ReliefF, Decision Trees, Random Forest Classification

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Authors: Anne C. Okwedadi, Samson Ng’ambi, Ian Jefferson

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Collapsible soils go through radical rearrangement of their particles when triggered by water, stress or/and vibration, causing loss of volume. This loss of volume in soil as seen in foundation failures has caused millions of dollars’ worth of damages to public facilities and infrastructure and so has an adverse effect on the society and people. Despite these consequences and the several studies that are available, more research is still required in the study of soil collapsibility. Discerning the pedogenesis (formation) of soils and investigating the combined effects of the different geological soil properties is key to elucidating and quantifying soils collapsibility. This study presents a novel laboratory testing regime that would be undertaken on soil samples where the effects of soil type, compactive variables (moisture content, density, void ratio, degree of saturation) and loading are analyzed. It is anticipated that results obtained would be useful in mapping the trend of the combined effect thus the basis for evaluating soil collapsibility or collapse potentials encountered in construction with volume loss problems attributed to collapse.

Keywords: Collapsible soil, Geomorphological process, Soil Collapsibility properties, Soil test.

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Authors: Priyanka Malik A, Rishu Chaujar B, Mridula Gupta C, R.S. Gupta D

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In this paper, for the first time, a two-dimensional (2D) analytical drain current model for sub-100 nm multi-layered gate material engineered trapezoidal recessed channel (MLGMETRC) MOSFET: a novel design is presented and investigated using ATLAS and DEVEDIT device simulators, to mitigate the large gate leakages and increased standby power consumption that arise due to continued scaling of SiO2-based gate dielectrics. The twodimensional (2D) analytical model based on solution of Poisson-s equation in cylindrical coordinates, utilizing the cylindrical approximation, has been developed which evaluate the surface potential, electric field, drain current, switching metric: ION/IOFF ratio and transconductance for the proposed design. A good agreement between the model predictions and device simulation results is obtained, verifying the accuracy of the proposed analytical model.

Keywords: ATLAS, DEVEDIT, NJD, MLGME- TRCMOSFET.

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: Indah Kurniawaty, Yoki Yulizar, Haryo Satrya Oktaviano, Adam Kusuma Rianto

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Magnesium oxide nanoparticles (MgO NP) were successfully synthesized in this study using a one-pot green synthesis mediated by Calliandra calothyrsus leaf extract (CLE). CLE was prepared by maceration of the leaf using methanol with a ratio of 1:5 for 7 days. Secondary metabolites in CLE, such as alkaloids and flavonoids, served as a weak base provider and capping agent in the formation of MgO NP. CLE Fourier Transform Infra-Red (FTIR) spectra peak at 3255 cm-1, 1600 cm-1, 1384 cm-1, 1205 cm-1, 1041 cm-1, and 667 cm-1 showing the presence of vibrations O-H stretching, N-H bending, C-C stretching, C-N stretching and N-H wagging. During the experiment, different CLE volumes and calcined temperatures were used, resulting in a variety of structures. Energy Dispersive X-ray Spectrometer (EDS) and FTIR were used to characterize metal oxide particles. MgO diffraction patterns at 2θ of 36.9°; 42.9°; 62.2°; 74.6°; and 78.5° can be assigned to crystal planes (111), (200), (220), (311), and (222), respectively. Scanning Electron Microscopy (SEM) was used to characterize the surface morphology. The morphology ranged from sphere to flower-like resulting in crystallite sizes of 28 nm, 23 nm, 12 nm, and 9 nm.

Keywords: Calliandra calothyrsus, green-synthesis, magnesium oxide, nanoparticle.

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Authors: Bobbie Green, James A. Nelson

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Innovations in technology have created new ethical challenges. Essential use of electronic communication in the workplace has escalated at an astronomical rate over the past decade. As such, legal and ethical dilemmas confronted by both the employer and the employee concerning managerial control and ownership of einformation have increased dramatically in the USA. From the employer-s perspective, ownership and control of all information created for the workplace is an undeniable source of economic advantage and must be monitored zealously. From the perspective of the employee, individual rights, such as privacy, freedom of speech, and freedom from unreasonable search and seizure, continue to be stalwart legal guarantees that employers are not legally or ethically entitled to abridge in the workplace. These issues have been the source of great debate and the catalyst for legal reform. The fine line between ethical and legal has been complicated by emerging technologies. This manuscript will identify and discuss a number of specific legal and ethical issues raised by the dynamic electronic workplace and conclude with suggestions that employers should follow to respect the delicate balance between employees- legal rights to privacy and the employer's right to protect its knowledge systems and infrastructure.

Keywords: Information, ethics, legal, privacy

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Authors: Simon Huston, Ebraheim Lahbash, Ali Parsa

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The development of the United Arab Emirates (UAE) into a regional trade, tourism, finance and logistics hub has transformed its real estate markets. However, speculative activity and price volatility remain concerns. UAE residential market values (MV) are exposed to fluctuations in capital flows and migration which, in turn, are affected by geopolitical uncertainty, oil price volatility and global investment market sentiment. Internally, a complex interplay between administrative boundaries, land tenure, building quality and evolving location characteristics fragments UAE residential property markets. In short, the UAE Residential Valuation System (UAE-RVS) confronts multiple challenges to collect, filter and analyze relevant information in complex and dynamic spatial and capital markets. A robust (RVS) can mitigate the risk of unhelpful volatility, speculative excess or investment mistakes. The research outlines the institutional, ontological, dynamic and epistemological issues at play. We highlight the importance of system capabilities, valuation standard salience and stakeholders trust.

Keywords: Valuation, property rights, information, institutions, trust, salience.

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Authors: Melissa C. LaDuke

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The overarching purpose of this study was to determine the relationship between the current format of online delivery for Defense Acquisition University (DAU) courses and Air Force Acquisition (AFA) personnel participation. AFA personnel (hereafter named “student”) were particularly of interest, as they have been mandated to take anywhere from 3 to 30 online courses to earn various DAU specialization certifications. Participants in this qualitative case study were AFA personnel who pursued DAU certifications in science and technology management, program/contract management, and other related fields. Air Force personnel were interviewed about their experiences with online courses. The data gathered were analyzed and grouped into 12 major themes. The themes tied into the theoretical framework and addressed either teacher-centered or student-centered educational practices within DAU. Based on the results of the data analysis, various factors contributed to student perceptions of DAU courses to include the online course construct and relevance to their job. The analysis also found students want to learn the information presented but would like to be able to apply the information learned in meaningful ways.

Keywords: Educational theory, computer-based training, interview, student perceptions, online course design, teacher positionality.

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Authors: Karim Heidari

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Semantic Web Technologies enable machines to interpret data published in a machine-interpretable form on the web. At the present time, only human beings are able to understand the product information published online. The emerging semantic Web technologies have the potential to deeply influence the further development of the Internet Economy. In this paper we propose a scenario based research approach to predict the effects of these new technologies on electronic markets and business models of traders and intermediaries and customers. Over 300 million searches are conducted everyday on the Internet by people trying to find what they need. A majority of these searches are in the domain of consumer ecommerce, where a web user is looking for something to buy. This represents a huge cost in terms of people hours and an enormous drain of resources. Agent enabled semantic search will have a dramatic impact on the precision of these searches. It will reduce and possibly eliminate information asymmetry where a better informed buyer gets the best value. By impacting this key determinant of market prices semantic web will foster the evolution of different business and economic models. We submit that there is a need for developing these futuristic models based on our current understanding of e-commerce models and nascent semantic web technologies. We believe these business models will encourage mainstream web developers and businesses to join the “semantic web revolution."

Keywords: E-Commerce, E-Business, Semantic Web, XML.

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Authors: Khalid A. Al-Afandy, El-Sayyed El-Rabaie, Osama Salah, Ahmed El-Mhalaway

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This paper presents a high secure data hiding technique using image cropping and Least Significant Bit (LSB) steganography. The predefined certain secret coordinate crops will be extracted from the cover image. The secret text message will be divided into sections. These sections quantity is equal the image crops quantity. Each section from the secret text message will embed into an image crop with a secret sequence using LSB technique. The embedding is done using the cover image color channels. Stego image is given by reassembling the image and the stego crops. The results of the technique will be compared to the other state of art techniques. Evaluation is based on visualization to detect any degradation of stego image, the difficulty of extracting the embedded data by any unauthorized viewer, Peak Signal-to-Noise Ratio of stego image (PSNR), and the embedding algorithm CPU time. Experimental results ensure that the proposed technique is more secure compared with the other traditional techniques.

Keywords: Steganography, stego, LSB, crop.

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Authors: Morteza Talebi, Jianan Wang, Zhihua Qu

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The security of power systems against malicious cyberphysical data attacks becomes an important issue. The adversary always attempts to manipulate the information structure of the power system and inject malicious data to deviate state variables while evading the existing detection techniques based on residual test. The solutions proposed in the literature are capable of immunizing the power system against false data injection but they might be too costly and physically not practical in the expansive distribution network. To this end, we define an algebraic condition for trustworthy power system to evade malicious data injection. The proposed protection scheme secures the power system by deterministically reconfiguring the information structure and corresponding residual test. More importantly, it does not require any physical effort in either microgrid or network level. The identification scheme of finding meters being attacked is proposed as well. Eventually, a well-known IEEE 30-bus system is adopted to demonstrate the effectiveness of the proposed schemes.

Keywords: Algebraic Criterion, Malicious Cyber-Physical Data Injection, Protection and Identification, Trustworthy Power System.

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Authors: Lianglin Xiong, Shouming Zhong, Mao Ye

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This paper considers the robust exponential stability issues for a class of uncertain switched neutral system which delays switched according to the switching rule. The system under consideration includes both stable and unstable subsystems. The uncertainties considered in this paper are norm bounded, and possibly time varying. Based on multiple Lyapunov functional approach and dwell-time technique, the time-dependent switching rule is designed depend on the so-called average dwell time of stable subsystems as well as the ratio of the total activation time of stable subsystems and unstable subsystems. It is shown that by suitably controlling the switching between the stable and unstable modes, the robust stabilization of the switched uncertain neutral systems can be achieved. Two simulation examples are given to demonstrate the effectiveness of the proposed method.

Keywords: Switched neutral system, exponential stability, multiple Lyapunov functional, dwell time technique, time-dependent switching rule.

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Authors: I. Turk Cakir, B. Hacisahinoglu, S. Kartal, A. Yilmaz, A. Yilmaz, Z. Uysal, O. Cakir

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In the search for new physics beyond the Standard Model, Flavour Changing Neutral Current (FCNC) is a good research field in terms of the observability at future colliders. Increased Higgs production with higher energy and luminosity in colliders is essential for verification or falsification of our knowledge of physics and predictions, and the search for new physics. Prospective electron-proton collider constituent of the Future Circular Collider project is FCC-eh. It offers great sensitivity due to its high luminosity and low interference. In this work, thq FCNC interaction vertex with off-shell top quark decay at electron-proton colliders is studied. By using MadGraph5_aMC@NLO multi-purpose event generator, observability of tuh and tch couplings are obtained with equal coupling scenario. Upper limit on branching ratio of tree level top quark FCNC decay is determined as 0.012% at FCC-eh with 1 ab ^−1 luminosity.

Keywords: FCC, FCNC, Higgs Boson, Top Quark.

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Authors: Xiao Yihong, Yu Kexin, Burra Venkata Durga Kumar

Abstract:

With the accelerating process of urbanization, the problem of urban road congestion is becoming more and more serious. Intelligent transportation system combining distributed and artificial intelligence has become a research hotspot. As the core development direction of the intelligent transportation system, Cooperative Intelligent Transportation System (C-ITS) integrates advanced information technology and communication methods and realizes the integration of human, vehicle, roadside infrastructure and other elements through the multi-agent distributed system. By analyzing the system architecture and technical characteristics of C-ITS, the paper proposes a distributed multi-agent C-ITS. The system consists of Roadside Subsystem, Vehicle Subsystem and Personal Subsystem. At the same time, we explore the scalability of the C-ITS and put forward incorporating local rewards in the centralized training decentralized execution paradigm, hoping to add a scalable value decomposition method. In addition, we also suggest introducing blockchain to improve the safety of the traffic information transmission process. The system is expected to improve vehicle capacity and traffic safety.

Keywords: Distributed system, artificial intelligence, multi-agent, Cooperative Intelligent Transportation System.

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Authors: Vijay Janyani, Trevor M. Benson, Ana Vukovic

Abstract:

A time-domain numerical model within the framework of transmission line modeling (TLM) is developed to simulate electromagnetic pulse propagation inside multiple microcavities forming photonic crystal (PhC) structures. The model developed is quite general and is capable of simulating complex electromagnetic problems accurately. The field quantities can be mapped onto a passive electrical circuit equivalent what ensures that TLM is provably stable and conservative at a local level. Furthermore, the circuit representation allows a high level of hybridization of TLM with other techniques and lumped circuit models of components and devices. A photonic crystal structure formed by rods (or blocks) of high-permittivity dieletric material embedded in a low-dielectric background medium is simulated as an example. The model developed gives vital spatio-temporal information about the signal, and also gives spectral information over a wide frequency range in a single run. The model has wide applications in microwave communication systems, optical waveguides and electromagnetic materials simulations.

Keywords: Computational Electromagnetics, Numerical Simulation, Transmission Line Modeling.

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Authors: Ivan Živanović, Žužana Vaštag, Senka Popović, Ljiljana Popović, Draginja Peričin

Abstract:

The present work represents an investigation of the hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein isolate (PuOC PI) by pepsin. To examine the effectiveness and suitability of pepsin towards PuOC PI the kinetic parameters for pepsin on PuOC PI were determined and then, the hydrolysis process was studied using Response Surface Methodology (RSM). The hydrolysis was carried out at temperature of 30°C and pH 3.00. Time and initial enzyme/substrate ratio (E/S) at three levels were selected as the independent parameters. The degree of hydrolysis, DH, was mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3 mA/mg proteins. Since the proposed second-order polynomial model showed good fit with the experimental data (R2 = 0.9822), the obtained mathematical model could be used for monitoring the hydrolysis of PuOC PI by pepsin, under studied experimental conditions, varying the time and initial E/S. To achieve the highest value of DH (39.13 %), the obtained optimum conditions for time and initial E/S were 30 min and 1.024 mA/mg proteins.

Keywords: Enzymatic hydrolysis, Pepsin, Pumpkin (CucurbitaPepo L.) oil cake protein isolate, Response surface methodology.

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Authors: Sajjad Hashemi, Seyyed Yasser Hashemi

Abstract:

In today's world, success of most systems depend on the use of new technologies and information technology (IT) which aimed to increase efficiency and satisfaction of users. One of the most important systems that use information technology to deliver services is the education system. But for educational services in the form of E-learning systems, hardware and software equipment should be containing high quality, which requires substantial investment. Because the vast majority of educational establishments can not invest in this area so the best way for them is reducing the costs and providing the E-learning services by using cloud computing. But according to the novelty of the cloud technology, it can create challenges and concerns that the most noted among them are security issues. Security concerns about cloud-based E-learning products are critical and security measures essential to protect valuable data of users from security vulnerabilities in products. Thus, the success of these products happened if customers meet security requirements then can overcome security threats. In this paper tried to explore cloud computing and its positive impact on E- learning and put main focus to identify security issues that related to cloud-based E-learning efforts which have been improve security and provide solutions in management challenges.

Keywords: Cloud computing, E-Learning, Security.

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